Exploring Azure Active Directory Attack Surface : Enumerating Authentication Methods with Open-Source Intelligence Tools

Abstract
Azure Active Directory (Azure AD) is Microsoft’s identity and access management service used globally by 90 per cent of Fortune 500 companies and many other organisations. Recent attacks by nation-state adversaries have targeted these organisations by exploiting known attack vectors. In this paper, open-source intelligence (OSINT) is gathered from organisations using Azure AD to explore the current attack surface. OSINT is collected from Fortune 500 companies and top 2000 universities globally. The collected OSINT includes authentication methods used by the organisation and the full name and phone number of the primary technical contact. The findings reveal that most organisations are using Azure AD and that majority of these organisations are using authentication methods exploited during the recent attacks by nation-state adversaries.
Main Authors
Format
Conferences Conference paper
Published
2022
Subjects
Publication in research information system
Publisher
SCITEPRESS Science And Technology Publications
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202303032006Käytä tätä linkitykseen.
Parent publication ISBN
978-989-758-569-2
Review status
Peer reviewed
ISSN
2184-4992
DOI
https://doi.org/10.5220/0011077100003179
Conference
International Conference on Enterprise Information Systems
Language
English
Is part of publication
ICEIS 2022 : Proceedings of the 24th International Conference on Enterprise Information Systems : Volume 2
Citation
  • Syynimaa, N. (2022). Exploring Azure Active Directory Attack Surface : Enumerating Authentication Methods with Open-Source Intelligence Tools. In J. Filipe, M. Smialek, A. Brodsky, & S. Hammoudi (Eds.), ICEIS 2022 : Proceedings of the 24th International Conference on Enterprise Information Systems : Volume 2 (pp. 142-147). SCITEPRESS Science And Technology Publications. https://doi.org/10.5220/0011077100003179
License
CC BY-NC-ND 4.0Open Access
Copyright© 2022 by SCITEPRESS – Science and Technology Publications, Lda.

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